Three-dimensional human facial morphologies as robust aging markers.

Abstract:

:Aging is associated with many complex diseases. Reliable prediction of the aging process is important for assessing the risks of aging-associated diseases. However, despite intense research, so far there is no reliable aging marker. Here we addressed this problem by examining whether human 3D facial imaging features could be used as reliable aging markers. We collected > 300 3D human facial images and blood profiles well-distributed across ages of 17 to 77 years. By analyzing the morphological profiles, we generated the first comprehensive map of the aging human facial phenome. We identified quantitative facial features, such as eye slopes, highly associated with age. We constructed a robust age predictor and found that on average people of the same chronological age differ by ± 6 years in facial age, with the deviations increasing after age 40. Using this predictor, we identified slow and fast agers that are significantly supported by levels of health indicators. Despite a close relationship between facial morphological features and health indicators in the blood, facial features are more reliable aging biomarkers than blood profiles and can better reflect the general health status than chronological age.

journal_name

Cell Res

journal_title

Cell research

authors

Chen W,Qian W,Wu G,Chen W,Xian B,Chen X,Cao Y,Green CD,Zhao F,Tang K,Han JD

doi

10.1038/cr.2015.36

subject

Has Abstract

pub_date

2015-05-01 00:00:00

pages

574-87

issue

5

eissn

1001-0602

issn

1748-7838

pii

cr201536

journal_volume

25

pub_type

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